Visual SLAM with a Multi-Camera Rig

Abstract

Camera-based simultaneous localization and mapping or visual SLAM has
received much attention recently. Typically single cameras, multiple
cameras in a stereo setup or omni-directional cameras are used. We propose
a different approach, where multiple cameras can be mounted on a robot in
an arbitrary configuration. Allowing the cameras to face in different
directions yields better constraints than single cameras or stereo setups
can provide, simplifying the reconstruction of large-scale environments.
And in contrast to omni-directional sensors, the available resolution can
be focused on areas of interest depending on the application. We describe
a sparse SLAM approach that is suitable for real-time reconstruction from
such multi-camera configurations. We have implemented the system and show
experimental results in a large-scale environment, using a custom made
eight-camera rig.